Two Strategies to Avoid Overfitting in Feedforward Networks

Author:

Schittenkopf Christian,Deco Gustavo,Brauer Wilfried

Publisher

Elsevier BV

Subject

Artificial Intelligence,Cognitive Neuroscience

Reference23 articles.

1. Adaptive Decorrelation;Almeida;Artificial Neural Networks,1992

2. Barlow, H. (1959). Sensory Mechanism, the Reduction of Redundancy and Intelligence. In National Physical Laboratory Symposium N. 10: The Mechanization of Thought Processes. London: HMSO.

3. Unsupervised Learning;Barlow;Neural Computation,1989

4. Bridle, J. (1990). Training Stochastic Model Recognition Algorithms as Networks Can Lead to Maximum Mutual Information Estimation of Parameters. In D.S. Touretzky (Ed.), Advances in Neural Information Processing II. San Mateo: Morgan Kaufmann.

5. Bridle, J., MacKay, D., & Heating, A. (1992). Unsupervised Classifiers, Mutual Information and “Phantom Targets”. In J.E. Moody, S.J. Hawson, & R.P. Lippmann (Eds.), Advances in Neural Information Processing IV. San Mateo: Morgan Kaufmann.

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